Innoviz Technologies

Field Application Engineer – Biz' Dev' Team (Silicon Valley)

Innoviz Technologies  •  Santa Clara, CA (Onsite)  •  2 months ago
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Job Description

Innoviz Technologies supplies safety-critical, high-performance LiDAR sensors for assisted driving systems, autonomous robotaxis, and various smart infrastructure applications.

We are looking for a highly motivated and self-driven individual to join our North American business team to be the technical face in front of customers who are solving cutting-edge problems in today’s autonomy revolution.

Your mission would be to support existing customers and assist in securing new business opportunities by solving technical product integration challenges in the field. This role would closely interact with product, engineering, test & validation, and operations teams at Innoviz HQ in Israel and operate as the technical bridge to the North American sales team.

What you'll do

  • Lead all customer-facing product demonstration activities for North American market verticals including autonomous vehicles, intelligent transportation systems (ITS), and security & surveillance solutions
  • Execute field tests at customer sites to help track Innoviz LiDAR range performance and collect datasets requested during commercial engagements with automotive OEMs and robotaxi providers
  • Help create data parsing tools, scripts, and converters to assist customers in automating analysis of field datasets
  • Be the first line of service to help troubleshoot product HW & SW issues both remotely and at customer sites. Help create innovative technical solutions on-the-fly to unblock customer bottlenecks.
  • Own the sales team demo vehicle integration to aid in showcasing the latest product performance and support technical marketing efforts to highlight KPIs customers see as beneficial
  • Track and share valuable, market-specific customer feedback to Innoviz HQ for continuous product improvement
  • Recommend product documentation improvements to Innoviz HQ to optimize the customer experience including datasheets, user manuals, technical resources, etc.

Requirements

  • BS or MS in Physics, Computer Science, Electrical Engineering, Computer Engineering, or Mechanical Engineering
  • Minimum 2 years of technical experience after graduation in HW/SW development and/or support roles
  • Versatile in Hardware & Software including C++, Python, ROS with experience in embedded systems

What We Need to See:

  • Located in the Silicon Valley Region
  • “Hands-On” with a willingness to travel up to 25% within US & Canada
  • Discipline and patience to resolve highly technical customer issues in a timely manner

Advantage:

  • Prior experience in robotics, artificial intelligence, perception, or automotive sensing
  • Prior experience in the LiDAR or optronics industry
  • Prior experience in photonics including lasers (EEL, fiber, VCSELs) or photodetectors (SPAD, SiPM, APD)

Eligibility requirement:

Due to employment regulations, we can only consider candidates who are U.S. citizens or Green Card holders for this position.

Interested in being part of the future of autonomous driving? Apply now.

Innoviz Technologies is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Innoviz Technologies

About Innoviz Technologies

Innoviz is a global leader in LiDAR technology, working towards a future with safe autonomous vehicles on the world’s roads. Innoviz’s LiDAR and perception software “see” better than a human driver and reduce the possibility of error, meeting the automotive industry's strictest expectations for performance and safety. Operating across the U.S., Europe, and Asia, Innoviz has been selected by internationally-recognized premium car brands for use in consumer vehicles as well as by other commercial and industrial leaders for a wide range of use cases. For more information, visit our website.

Industry
Automotive & Mobility
Company Size
201-500 employees
Headquarters
Santa Clara, California
Year Founded
2016
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